Infection of cattle with bovine paratuberculosis (i.e., Johne's disease) is caused by Mycobacterium avium ssp. paratuberculosis (MAP) and results in a chronic incurable gastroenteritis. This disease, which has economic ramifications for the cattle industry, is increasing in detected prevalence globally; subclinically infected animals can silently shed the bacterium into the environment for years, exposing contemporaries and hampering disease-control programs. The objective of the present study was to first quantify the genetic parameters for humoral response to MAP in dairy cattle. This was followed by a genome-based association analysis and subsequent downstream bioinformatic analyses from imputed whole genome sequence SNP data. After edits, ELISA test records were available on 136,767 cows; analyses were also undertaken on a subset of 33,818 of these animals from herds with at least 5 MAP ELISA-positive cows, with at least 1 of those positive cows being homebred. Variance components were estimated using univariate animal and sire linear mixed models. The heritability calculated from the animal model for humoral response to MAP using alternative phenotype definitions varied from 0.02 (standard error = 0.003) to 0.05 (standard error = 0.008). The genome-based associations were undertaken within a mixed model framework using weighted deregressed estimated breeding values as a dependent variable on 1,883 phenotyped animals that were >= 87.5% Holstein-Friesian. Putative susceptibility quantitative trait loci (QTL) were identified on Bos taurus autosome 1, 3, 5, 6, 8, 9, 10, 11, 13, 14, 18, 21, 23, 25, 26, 27, and 29; mapping the most significant SNP to genes within and overlapping these QTL revealed that the most significant associations were with the 10 functional candidate genes KALRN, ZBTB20, LPP, SLA2, FI3A1, LRCH3, DNAJC6, ZDHHC14, SNX1, and HAS2. Pathway analysis failed to reveal significantly enriched biological pathways, when both bovine-specific pathway data and human ortholog data were taken into account. The existence of genetic variation for MAP susceptibility in a large data set of dairy cows signifies the potential of breeding programs for reducing MAP susceptibility. Furthermore, the identification of susceptible QTL facilitates greater biological understanding of bovine paratuberculosis and potential therapeutic targets for future investigation. The novel molecular similarities identified between bovine paratuberculosis and human inflammatory bowel disease suggest potential for human therapeutic interventions to be translated to veterinary medicine and vice versa.

Twinning is a multifactorial trait influenced by both genetic and environmental factors that can negatively impact animal welfare and economic sustainability on commercial dairy operations. To date, using genetic selection as a tool for reducing twinning rates on commercial dairies has been proposed, but not yet implemented. In response to this market need, Zoetis (Kalamazoo, MI, USA) has developed a genomic prediction for twin pregnancies, and included it in a comprehensive multitrait selection index. The objectives of this study were to (1) describe a genetic evaluation for twinning in Holstein cattle, (2) demonstrate the efficacy of the predictions, (3) propose strategies to reduce twin pregnancies using this information. Data were retrieved from commercial dairies and provided directly by producers upon obtaining their permission. The twin pregnancies trait (TWIN) was defined as a pregnancy resulting in birth or abortion of twin calves, classified as a binary (0,1) event, and analysed using a threshold animal model. Predictions for a subset of cows were compared to their on-farm twin records. The heritability for twin pregnancies was 0.088, and genomic predicted transmitting abilities ((g)PTAs) ranged from −7.45–20.79. Genetic correlations between TWIN and other traits were low, meaning that improvement for TWIN will not negatively impact improvement for other traits. TWIN was effectively demonstrated to identify cows most and least likely to experience a twin pregnancy in a given lactation, regardless of reproductive protocol used. Effective inclusion of the prediction in a multitrait selection index offers producers a comprehensive tool to inform selection and management decisions. When combined with sound management practices, this presents a compelling opportunity for dairy producers to proactively reduce the incidence of twin pregnancies on commercial dairy operations.